Functional Prediction of Hypothetical Proteins from Shigella flexneri and Validation of the Predicted Models by Using ROC Curve Analysis

• Published in: Genomics & informatics 2018, 16(4), , pp.26-26
• Main Authors: Gazi, Md Amran, Mahmud, Sultan, Fahim, Shah Mohammad, Kibria, Mohammad Golam, Palit, Parag, Islam, Md Rezaul, Rashid, Humaira, Das, Subhasish, Mahfuz, Mustafa, Ahmeed, Tahmeed
• Format: Article
• Language: English
• Subjects: Original; 자연과학일반
• ISSN: 1598-866X; 2234-0742; 2234-0742
• DOI: 10.5808/GI.2018.16.4.e26

Shigella spp. constitutes some of the key pathogens responsible for the global burden of diarrhoeal disease. With over 164 million reported cases per annum, shigellosis accounts for 1.1 million deaths each year. Majority of these cases occur among the children of the developing nations and the emergence of multi-drug resistance Shigella strains in clinical isolates demands the development of better/new drugs against this pathogen. The genome of Shigella flexneri was extensively analyzed and found 4,362 proteins among which the functions of 674 proteins, termed as hypothetical proteins (HPs) had not been previously elucidated. Amino acid sequences of all these 674 HPs were studied and the functions of a total of 39 HPs have been assigned with high level of confidence. Here we have utilized a combination of the latest versions of databases to assign the precise function of HPs for which no experimental information is available. These HPs were found to belong to various classes of proteins such as enzymes, binding proteins, signal transducers, lipoprotein, transporters, virulence and other proteins. Evaluation of the performance of the various computational tools conducted using receiver operating characteristic curve analysis and a resoundingly high average accuracy of 93.6% were obtained. Our comprehensive analysis will help to gain greater understanding for the development of many novel potential therapeutic interventions to defeat Shigella infection.